Abstract--This paper considers the noncooperative maximization of mutual information in the vector Gaussian interference channel in a fully distributed fashion via game theory. Thi...
Interactive algorithm visualizations (AVs) are powerful tools for teaching and learning concepts that are difficult to describe with static media alone. However, while countless A...
Saleema Amershi, Giuseppe Carenini, Cristina Conat...
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
This paper presents a basic framework for applying static task scheduling techniques to arbitrarily-structured task systems whose targeted execution environment is comprised of fi...
We consider a dynamic load balancing scenario in which users allocate resources in a non-cooperative and selfish fashion. The perceived performance of a resource for a user decre...
Heiner Ackermann, Simon Fischer, Martin Hoefer, Ma...